This document explores the details of the GeoDjango Model API. Throughout this\nsection, we’ll be using the following geographic model of a ZIP code and\nof a Digital Elevation Model as our examples:
\nfrom django.contrib.gis.db import models\n\n\nclass Zipcode(models.Model):\n code = models.CharField(max_length=5)\n poly = models.PolygonField()\n\n\nclass Elevation(models.Model):\n name = models.CharField(max_length=100)\n rast = models.RasterField()\nSpatiala fält består av en serie geometriska fälttyper och en rasterfälttyp. Var och en av geometrifälttyperna motsvarar OpenGIS Simple Features-specifikationen [1]. Det finns ingen sådan standard för rasterdata.
\nGeometryFieldLink to this heading#Basklass för geometriska fält.
\nPointFieldLink to this heading#Lagrar en Point.
LineStringFieldLink to this heading#Lagrar en LineString.
PolygonFieldLink to this heading#Lagrar en Polygon.
MultiPointFieldLink to this heading#Lagrar en MultiPoint.
MultiLineStringFieldLink to this heading#Lagrar en MultiLineString.
MultiPolygonFieldLink to this heading#Lagrar en MultiPolygon.
GeometryCollectionFieldLink to this heading#Lagrar en GeometryCollection.
RasterFieldLink to this heading#Lagrar en GDALRaster.
RasterField är för närvarande endast implementerat för PostGIS backend.
Förutom de vanliga Alternativ för fält som finns tillgängliga för Django-modellfält, har spatiala fält följande ytterligare alternativ. Alla är valfria.
\nsridLink to this heading#Ställer in SRID [2] (Spatial Reference System Identity) för geometrifältet till det angivna värdet. Standardvärdet är 4326 (även känt som WGS84, enheterna är i grader av longitud och latitud).
\nChoosing an appropriate SRID for your model is an important decision that the\ndeveloper should consider carefully. The SRID is an integer specifier that\ncorresponds to the projection system that will be used to interpret the data in\nthe spatial database. [3] Projection systems give the context to the\ncoordinates that specify a location. Although the details of geodesy are\nbeyond the scope of this documentation, the general problem is that the earth\nis spherical and representations of the earth (e.g., paper maps, web maps) are\nnot.
\nMost people are familiar with using latitude and longitude to reference a\nlocation on the earth’s surface. However, latitude and longitude are angles,\nnot distances. In other words, while the shortest path between two points on a\nflat surface is a straight line, the shortest path between two points on a\ncurved surface (such as the earth) is an arc of a great circle.\n[4]
\nThus, additional computation is required to obtain distances in planar units\n(e.g., kilometers and miles). Using a geographic coordinate system may\nintroduce complications for the developer later on. For example, SpatiaLite\ndoes not have the capability to perform distance calculations between\ngeometries using geographic coordinate systems, e.g. constructing a query to\nfind all points within 5 miles of a county boundary stored as WGS84. [5]
\nPortions of the earth’s surface may projected onto a two-dimensional, or\nCartesian, plane. Projected coordinate systems are especially convenient for\nregion-specific applications, e.g., if you know that your database will only\ncover geometries in North Kansas, then you may consider using projection\nsystem specific to that region. Moreover, projected coordinate systems are\ndefined in Cartesian units (such as meters or feet), easing distance\ncalculations.
\n\nMer om detta:
\nspatialreference.org: En Django-driven databas med rumsliga referenssystem.
The State Plane Coordinate System: A website covering the various\nprojection systems used in the United States. Much of the U.S. spatial\ndata encountered will be in one of these coordinate systems rather than\nin a geographic coordinate system such as WGS84.
rumsligt_indexLink to this heading#Defaults to True. Creates a spatial index for the given geometry\nfield.
Det finns ytterligare alternativ tillgängliga för Geometry-fält. Alla följande alternativ är valfria.
\ndimLink to this heading#This option may be used for customizing the coordinate dimension of the\ngeometry field. By default, it is set to 2, for representing two-dimensional\ngeometries. For spatial backends that support it, it may be set to 3 for\nthree-dimensional support.
\n\ngeografiLink to this heading#If set to True, this option will create a database column of\ntype geography, rather than geometry. Please refer to the\ngeography type section below for more\ndetails.
max_geom_collectionsLink to this heading#This option is forwarded to the form field generated for this model\nfield, bounding how many geometry collections may be contained in submitted\nWKB/WKT inputs before raising ValueError. Since spatial field\nassignments are lazy, it is also checked when values are accessed, e.g. when\nsaving an instance, but not when read from a database. It defaults to 198.
The geography type provides native support for spatial features represented\nwith geographic coordinates (e.g., WGS84 longitude/latitude). [6]\nUnlike the plane used by a geometry type, the geography type uses a spherical\nrepresentation of its data. Distance and measurement operations\nperformed on a geography column automatically employ great circle arc\ncalculations and return linear units. In other words, when ST_Distance\nis called on two geographies, a value in meters is returned (as opposed\nto degrees if called on a geometry column in WGS84).
Eftersom geografiska beräkningar kräver mer matematik är endast en delmängd av PostGIS rumsliga uppslagsord tillgängliga för den geografiska typen. I praktiken innebär detta att utöver distance lookups är endast följande ytterligare spatial lookups tillgängliga för geografiska kolumner:
\ntäckt av
täcken
Om du behöver använda en spatial lookup eller aggregat som inte stöder geografin som indata kan du använda databasfunktionen Cast för att konvertera geografikolumnen till en geometrityp i frågan:
from django.contrib.gis.db.models import PointField\nfrom django.db.models.functions import Cast\n\nZipcode.objects.annotate(geom=Cast("geography_field", PointField())).filter(\n geom__within=poly\n)\nFor more information, the PostGIS documentation contains a helpful section on\ndetermining when to use geography data type over geometry data type.
\nFotnoter
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